LDPC编码调制系统中基于反馈LLR均值的迭代解调/译码算法

该文针对LDPC码编码的BICM系统,提出一种对LDPC码译码器输出外附信息的计算方法进行改进的迭代解调/译码算法。与传统的解调/译码算法不同在于,该算法对每次BP迭代中译码器输出的各编码比特的外附LLR分别求均值后,再将其作为先验信息反馈给软解调器开始下次的迭代解调/译码。采用该方法可有效地减轻LDPC码在BP迭代过程中某些比特LLR值的振荡现象,从而使得传递给软解调器的外附信息更准确。仿真结果表明,和传统的两种迭代解调/译码算法相比,该算法能进一步提高LDPC编码BICM迭代系统的译码性能,而复杂度并无明显增加。     

一种适用于BICM-ID系统的迭代载波同步算法

在比特交织编码调制迭代译码(BICM-ID)系统中,针对低信噪比条件下传统的同步算法对频偏和相差估计精度较低的问题,提出了一种码辅助的迭代载波同步算法。该算法基于最大期望(EM)算法,并在此基础上加以改进,利用译码器输出的软信息,迭代的在载波同步和译码之间相互交换信息,实现同步和译码的联合处理。仿真结果表明,在译码器收敛的允许范围之内,提出的算法能够大幅提高同步参数的估计精度,在迭代次数达到8次时,BICM-ID系统的误比特率性能基本接近理想同步条件下的译码性能。     

一种短时延的Turbo码并行译码算法

由于迭代译码是Turbo码译码的主要特点,因而在译码的过程中会带来很大的时延.为了减小译码延时,本文将整块译码器分成w个子块,并且运用计算复杂度低的T-BCJR算法,在相邻的子块译码器之间相互运用边界分配值作为下一次迭代的初始值,而不是采用各相邻的子块之间重叠部分进行译码,故使译码延时下降为原来的1/w。     

LDPC码的交替迭代分层置信传播译码

低密度奇偶校验码(LDPC)通过迭代译码算法进行译码,例如置信传播算法(belief-propagation)便是其中一种译码方式。标准BP算法是并行译码,在更新所有校验节点及比特节点过程中,使用上一次迭代的更新信息。为了提高一定迭代次数下的收敛速度,在研究不同算法的基础上,如Layered BP算法(LBP)和Shuffled BP算法(SBP),通过改变节点的更新顺序,提出了改进的shuffled迭代译码算法。相对于普通的SBP算法,文章所提改进型SBP算法是传统置信传播收敛速度的两倍,并且在保持性能的同时降低复杂度。最后给出了CMMB标准下LDPC码的仿真结果。     

基于生成矩阵的LDPC/Turbo码的构造及内外迭代译码新技术

提出了一种新的LDPC／Turbo码（简称L／T码）,及采用内外迭代译码新技术的简便实用的译码器。L／T码将原来Turbo编码中的两个子编码器分别用RSC码和LDPC码来代替,并由一个交织器连接。解码采用软输入／软输出的最大后验概率算法迭代执行,利用外信息的传递,每个子译码器都可以充分利用另一个在上一步计算中得到的结果。仿真在加性白高斯信道下进行,并将其结果和传统方法进行了比较。     

基于SSCANL译码器的联合迭代检测译码算法

为了提升基于极化码的稀疏码多址接入（sparse code multiple access,SCMA）系统接收机性能,提出了基于简化软消除列表（simplify soft cancellation list,SSCANL）译码器的循环冗余校验（cyclic redundancy check,CRC）辅助联合迭代检测译码接收机方案。该方案中极化码译码器使用SSCANL译码算法,采用译码节点删除技术对软消除列表（soft cancellation list,SCANL）算法所需要的L次软消除译码（soft cancellation, SCAN）进行简化,通过近似删除冻结位节点,简化节点间软信息更新计算过程,从而降低译码算法的计算复杂度。仿真结果表明,SSCANL算法可获得与SCANL算法一致的性能,其计算复杂度与SCANL算法相比有所降低,码率越低,算法复杂度降低效果越好;且基于SSCANL译码器的CRC 辅助联合迭代检测译码接收机方案相较基于SCAN译码器的联合迭代检测译码（joint iterative detection and decoding based on SCAN decoder, JIDD-SCAN）方案、基于SCAN译码器的CRC辅助联合迭代检测译码（CRC aided joint iterative detection and decoding based on SCAN decoder,C-JIDD-SCAN）方案,在误码率为10^-4时,性能分别提升了约0.65 dB、0.59 dB。     

BCH-Turbo编码的设计与仿真实现

本文针对Turbo码在低信噪比下迭代次数多、译码时延长问题,在分析了Turbo码的编译码原理和算法基础上,提出一种可以有效降低平均迭代次数、减少译码时延的基于BCH迭代停止准则的Turbo码迭代译码的设计方案。本方案采用BCH码作为Turbo迭代译码的停止准则。并对每一个分量译码器结果都进行判断。可提前停止迭代。通过Monte Carlo仿真表明在AWGN信道下,误码率有所降低。Turbo码译码的平均迭代次数与交叉熵准则相比有明显下降。本文还分析了BCH码编码效率和分组长度的选择对系统性能的影响。     

不同译码器结构对Turbo码性能的影响

文章给出了两种译码顺序不同的Ｔｕｒｂｏ码译码器,并通过软判决维特比算法作译码业比较两种结构的译码效果。     

一种改进的多元LDPC码译码算法

在多元LDPC码的软判决译码算法中,迭代过程中没有使用判决结果和校验和中隐藏的一些信息,在判决结果中隐藏着稳定性信息,校验和中隐藏着变量节点的可靠度信息。从混合译码算法思路出发,借鉴硬判决译码算法中统计校验和的做法和联合迭代检测译码算法中的反馈调整思想,对FFT-BP译码算法进行了改进。改进算法利用迭代过程中的可靠性和稳定度信息,对由变量节点向校验节点传递的消息向量进行调整以使其提供更多正确信息。仿真结果表明,改进的译码算法在没有增加复杂度的前提下,提升了FFT-BP译码算法的性能,在不同参数设置下,性能改进在0.2 d B左右。     

基于多元LDPC码的迭代符号定时恢复

针对极低/低信噪比深空通信中传统符号定时恢复难的问题,本文提出了一种联合符号定时恢复与多元LDPC迭代译码的方案。该方案将Mueller& Muller符号定时恢复算法与迭代译码方法相结合,对符号周期内的动态时延进行校正。根据译码反馈信息的不同,迭代译码方法可分为基于译码硬信息和译码软信息两种迭代方法。仿真结果表明,在高阶调制、低信噪比和动态时延下,基于两种迭代方法的符号定时恢复算法均取得了接近于理想情况的性能,且收敛速度快,适合于工程实现。其中,由于基于译码软信息迭代的符号定时恢复算法保留了更完整的概率信息,因而性能更优。      

Turbo decoder using local subsidiary maximum likelihood decoding in prior estimation of the extrinsic information

A new technique for turbo decoder is proposed by using a local subsidiary maximum likelihood decoding and a probability distributions family for the extrinsic information. The optimal distribution of the extrinsic information is dynamically specified for each component decoder.The simulation results show that the iterative decoder with the new technique outperforms that of the decoder with the traditional Gaussian approach for the extrinsic information under the same conditions.     

Correction of extrinsic information for iterative decoding in a serially concatenated multiuser DS-CDMA system

The system under study is a coded asynchronous DS-CDMA system with orthogonal modulation in time-varying Rayleigh fading multipath channels. Information bits are convolutionally encoded, block interleaved, and mapped to M-ary orthogonal Walsh codes, where the last step is essentially a process of block coding. This paper aims at tackling the problem of joint iterative decoding of this serially concatenated inner block code and outer convolutional code and estimating frequency-selective fading channels in multiuser environments. The (logarithm) maximum a posteriori probability, (Log)-MAP criterion is used to derive the iterative decoding schemes. In our system, the soft output from inner block decoder is used as a priori information for the outer decoder. The soft output from outer convolutional decoder is used for two purposes. First, it may be fed back to the inner decoder as extrinsic information for the systematic bits of the Walsh codeword. Secondly, it is utilized for channel estimation and multiuser detection (MUD). We also show that the inner decoding can be accomplished without extrinsic information, and in some cases, e.g., when the system is heavily loaded, yields better performance than the decoding with unprocessed extrinsic information. This implies the need for correcting the extrinsic information obtained from outer decoder. Different schemes are examined and compared numerically, and it is shown that iterative decoding with properly corrected extrinsic information or with non-extrinsic/extrinsic adaptation enables the system to operate reliably in the presence of severe multiuser interference, especially when the inner decoding is assisted by decision directed channel estimation and interference cancellation techniques.     

迭代结构的信源信道联合解码及其简化算法

信源信道联合解码算法中的迭代信道解码需要进行比特似然值和概率值转换,以及联乘、累加运算,增加了信道解码的计算复杂度,该文针对这一问题,直接利用信道解码的比特硬判决值和参数的先验概率,估计比特的外信息,用于迭代信道解码。基于高斯-马尔可夫信源参数的仿真实验表明,该简化算法大大降低了迭代信道解码算法的计算复杂度。与独立解码算法相比,简化的联合解码算法明显改善了接收参数的信噪比,同时不会明显降低原迭代结构解码算法的性能。     

Complexity Reduction in SISO Decoding of Block Codes

SISO decoding for block codes can be carried out based on a trellis representation of the code. However, the complexity entailed by such decoding is most often prohibitive and thus prevents practical implementation. This paper examines a new decoding scheme based on the soft-output Viterbi algorithm (SOVA) applied to a sectionalized trellis for linear block codes. The computational complexities of the new SOVA decoder and of the conventional SOVA decoder, based on a bit-level trellis, are theoretically analyzed and derived for different linear block codes. These results are used to obtain optimum sectionalizations of a trellis for SOVA. For comparisons, the optimum sectionalizations for Maximum A Posteriori (MAP) and Maximum Logarithm MAP (Max-Log-MAP) algorithms, and their corresponding computational complexities are included. The results confirm that the new SOVA decoder is the most computationally efficient SISO decoder, in comparisons to MAP and Max-Log-MAP algorithms. The simulation results of the bit error rate (BER) performance, assuming binary phase -- shift keying (BPSK) and additive white Gaussian noise (AWGN) channel, demonstrate that the performance of the new decoding scheme is not degraded. The BER performance of iterative SOVA decoding of serially concatenated block codes shows no difference in the quality of the soft outputs of the new decoding scheme and of the conventional SOVA.     

Gear-Shift Decoding

This paper considers a class of iterative message-passing decoders for low-density parity-check codes in which the decoder can choose its decoding rule from a set of decoding algorithms at each iteration. Each available decoding algorithm may have different per-iteration computation time and performance. With an appropriate choice of algorithm at each iteration, overall decoding latency can be reduced significantly, compared with standard decoding methods. Such a decoder is called a gear-shift decoder because it changes its decoding rule (shifts gears) in order to guarantee both convergence and maximum decoding speed (minimum decoding latency). Using extrinsic information transfer charts, the problem of finding the optimum (minimum decoding latency) gear-shift decoder is formulated as a computationally tractable dynamic program. The optimum gear-shift decoder is proved to have a decoding threshold equal to or better than the best decoding threshold among those of the available algorithms. In addition to speeding up software decoder implementations, gear-shift decoding can be applied to optimize a pipelined hardware decoder, minimizing hardware cost for a given decoder throughput.     

Soft-Output BEAST Decoding With Application to Product Codes

A Bidirectional Efficient Algorithm for Searching code Trees (BEAST) is proposed for efficient soft-output decoding of block codes and concatenated block codes. BEAST operates on trees corresponding to the minimal trellis of a block code and finds a list of the most probable codewords. The complexity of the BEAST search is significantly lower than the complexity of trellis-based algorithms, such as the Viterbi algorithm and its list generalizations. The outputs of BEAST, a list of best codewords and their metrics, are used to obtain approximate a posteriori probabilities (APPs) of the transmitted symbols, yielding a soft-input soft-output (SISO) symbol decoder referred to as the BEAST-APP decoder. This decoder is employed as a component decoder in iterative schemes for decoding of product and incomplete product codes. Its performance and convergence behavior are investigated using extrinsic information transfer (EXIT) charts and compared to existing decoding schemes. It is shown that the BEAST-APP decoder achieves performances close to the Bahl–Cocke–Jelinek–Raviv (BCJR) decoder with a substantially lower computational complexity.      

Joint decoding and carrier phase recovery algorithm for turbo codes

In this letter, we investigate the sensitivity of the iterative maximum a posteriori probability (MAP) decoder to carrier phase offsets and propose simple carrier phase recovery algorithms operating within the iterative MAP decoding iterations. The algorithms exploit the information contained in the extrinsic values generated within the iterative MAP decoder to perform carrier recovery, thus requiring low hardware complexity     

On turbo decoding of nonbinary codes

Symbol-by-symbol maximum a posteriori (MAP) decoding algorithms for nonbinary block and convolutional codes over an extension field GF(p ^a) are presented. Equivalent MAP decoding rules employing the dual code are given which are computationally more efficient for high-rate codes. It is shown that these algorithms meet all requirements needed for iterative decoding as the output of the decoder can be split into three independent estimates: soft channel value, a priori term and extrinsic value. The discussed algorithms are then applied to a parallel concatenated coding scheme with nonbinary component codes in conjunction with orthogonal signaling     

Iterative Source-Channel Decoding With Markov Random Field Source Models

We propose a joint source-channel decoding approach for multidimensional correlated source signals. A Markov random field (MRF) source model is used which exemplarily considers the residual spatial correlations in an image signal after source encoding. Furthermore, the MRF parameters are selected via an analysis based on extrinsic information transfer charts. Due to the link between MRFs and the Gibbs distribution, the resulting soft-input soft-output (SISO) source decoder can be implemented with very low complexity. We prove that the inclusion of a high-rate block code after the quantization stage allows the MRF-based decoder to yield the maximum average extrinsic information. When channel codes are used for additional error protection the MRF-based SISO source decoder can be used as the outer constituent decoder in an iterative source-channel decoding scheme. Considering an example of a simple image transmission system we show that iterative decoding can be successfully employed for recovering the image data, especially when the channel is heavily corrupted.